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Estimation of groundwater levels with vertical electrical sounding in the semiarid area of South Keerqin sandy aquifer, China
Journal of Applied Geophysics 83 (2012) 11–18
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Estimation of groundwater levels with vertical electrical sounding in the semiarid area of South Keerqin sandy aquifer, China Lining Song a, b, Jiaojun Zhu a,⁎, Qiaoling Yan a, Hongzhang Kang c a b c
State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China Graduate University of Chinese Academy of Sciences, Beijing 100039, China Shanghai Jiaotong University, Shanghai 200240, China
a r t i c l e
i n f o
Article history: Received 23 September 2011 Accepted 28 March 2012 Available online 6 April 2012 Keywords: Groundwater Soil electrical resistivity Manual measurement Wenner array Sandy aquifers
a b s t r a c t To develop a simple, accurate, and non-destructive method for estimating the groundwater level (GWL) in an unconfined sandy aquifer, field measurements of soil electrical resistivity were conducted at the Daqinggou Ecological Station (DES) in 2005 and the Experimental Base of the Institute of Wind-Sand Land Improvement and Utilization (IWLIU) in 2009. The resistivity data were acquired through a series of vertical electrical soundings (VES) using a Wenner array. For comparison with the VES method, the GWLs were also manually monitored in wells. The results showed that the thirty VES profiles decreased or first increased and then decreased with increasing electrode spacing (i.e., becoming more conductive with depth). The depth of the GWL was obtained by calculating the turning points, as inferred from inflections in the apparent resistivity profiles. The GWL variations between the VES method and manual measurement ranged from 0.22 to 1.03 m at the DES, with a mean value of 0.52 m, and from 0.03 to 0.82 m at the IWLIU, with a mean value of 0.10 m. The significant differences between the GWLs obtained by the VES method and manual measurement at the DES were due to the higher GWLs with capillary action; there were no significant differences in the GWLs obtained at the IWLIU. The linear regression coefficient of determination was 0.97 for the IWLIU GWL values, indicating a good agreement between the VES method and manual measurements. Therefore, we conclude that the VES method is a sound measuring tool for estimating GWLs in unconfined sandy aquifers when the GWL is sufficiently deep (e.g., GWL > 3.98 m). © 2012 Elsevier B.V. All rights reserved.
1. Introduction Groundwater is one of the most valuable natural resources (Konig and Weiss, 2009; Wood, 2002) and an important geological agent in the transport of mass and energy within the earth (Llamas, 1987), providing a wide variety of ecological and social services (DÖll, 2009; Houben and Weihe, 2010; Laio et al., 2009). In arid and semiarid areas, surface water resources are generally scarce and highly unreliable; therefore, groundwater is often the primary water resource in these areas (Scanlon et al., 2006). Groundwater level (GWL) is an essential factor related to eco-environmental problems, such as oasis degeneration caused by declining groundwater levels and land salinification due to rising groundwater levels. Thus, groundwater level monitoring is particularly important for sustainable groundwater resource management in arid and semiarid areas. The traditional method for monitoring GWL is the collection of measurements from a limited number of often widely spaced piezometers or observation wells (Doolittle et al., 2006). This method ⁎ Corresponding author at: Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang110016. Tel.: +86 24 83970342; fax: +86 24 83970300. E-mail address: [email protected] (J. Zhu). 0926-9851/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.jappgeo.2012.03.011
requires large amounts of manpower and material resources; limitations in the number of wells drilled may thus lead to the inaccurate estimation of groundwater levels (Bian et al., 2009; Buchanan and Triantafilis, 2009). Additionally, extensive well drilling may result in damage to the site, especially in arid and semiarid sandy areas (Tabbagh et al., 2000). Therefore, traditional methods cannot typically be applied to monitor the GWL efficiently in such areas. In contrast, geophysical methods are currently receiving increasing attention for GWL monitoring due to their noninvasive nature and the ability to investigate an entire soil volume (Tabbagh et al., 2000). Among these geophysical methods, ground-penetrating radar (GPR), remote sensing, and electrical resistivity have been widely used in groundwater exploration. GPR can provide high-resolution subsurface images of the shallow subsurface (Doolittle et al., 2006; Lambot et al., 2008; Pyke et al., 2008; Rucker and Ferré, 2003); however, this method is not applicable when the GWL of a study area is deeper than 30 m (Liang et al., 2002). Remote sensing has the advantages of spatial, spectral and temporal availabilities and the manipulation of data covering large areas in a short time (Sener et al., 2005), but the precision of remote sensing is low by visual interpretation or conventional statistical methods, which limits its application in GWL estimation.
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Originally investigated for grounding and lightning prevention/ protection systems, soil electrical resistivity (or soil resistivity) is an important parameter that reflects soil physical properties and subsurface structure (Sakamoto, 2001; Sakamoto and Sekiguchi, 2001; Samouëlian et al., 2005; Zhu et al., 2005; 2007). Vertical electrical sounding (VES) is a geoelectrical method for measuring vertical alterations in soil resistivity, which has been recognized as being well suited for the subsurface investigation of geologic environments (Nejad, 2009). Generally, there are three electrode configurations that are applied in VES profiling: the Wenner, Schlumberger, and dipole–dipole arrays (Rucker et al., 2009). Among these, the Wenner array has the simplest geometry (Clayton et al., 1995) and is quicker and easier to operate than the Schlumberger array. The dipole–dipole array method yields lower signal strength compared with the Wenner and Schlumberger arrays (Loke, 2001). In addition, the Wenner array is the most accurate for the measurement of apparent resistivity (Del Alamo, 1991; Gonos and Stathopulos, 2005) and is useful in resolving vertical resistivity changes with depth (Loke, 2001). Therefore, VES with the Wenner array is widely used in soil science and groundwater investigation (Corwin and Lesch, 2005) for detecting soil salinity in precision agriculture (Corwin and Lesch, 2003), investigating groundwater pollution (Urish, 1983), mapping groundwater flow direction and velocity (White, 1994), and detecting soil cracking (Samouëlian et al., 2003). In previous studies, VES using Wenner arrays has been applied to determine soil resistivity (Zhu et al., 2005) and estimate soil water content within 1.50 m from the surface in pine plantations in sandy soils (Zhu et al., 2007). However, little information exists regarding whether VES with a Wenner array can be applied to the estimation of GWL in a sandy aquifer. The purpose of this study was to evaluate the use of VES with a Wenner array for the estimation of the GWL in a sandy aquifer and to determine the accuracy and usefulness of this method. 2. Materials and methods
Applied Ecology, Chinese Academy of Sciences (42°52′ N, 122°55′ E) and the Experimental Base of the Institute of Wind-Sand Land Improvement and Utilization (IWLIU), Liaoning Province, China (42°43′ N, 122°22′ E) (Fig. 1). The two sites are 25 km apart. The mean annual air temperature at both sites is 6.1 °C, and the minimum and maximum air temperatures (1954–2010) are −29.5 °C and 37.2 °C, respectively. The annual precipitation at both sites is 474 mm, with more than 60% occurring during June and August. The major soil type is classified in the Semiaripsamment taxonomic group, which is developed from sandy parent material through wind action (Zeng et al., 2009; Zhu et al., 2008). The vegetation in the study areas consists of Pinus sylvestris var. mongolica plantations and annual herbs (Zhao et al., 2004; Zhu et al., 2005). Based on landforms, vegetation cover types and soil characteristics, the sandy areas in the study areas were classified into low aeolian dunes, low mountains and hills, and high elevation alluvial flats. The current average groundwater levels are approximately 2.00 m and 5.54 m at the DES and the IWLIU, respectively. 2.2. Theory In the Wenner array, four electrodes were injected into the soil surface along a straight line at predetermined distances (a) (Fig. 2). The electrical resistance to current flow was measured between a pair of inner electrodes (P1 and P2 in Fig. 2) while electrical current flowed through the soil between a pair of outer electrodes (C1 and C2 in Fig. 2) (Corwin, 2008; Rhoades, 1976; Zhu et al., 2007). When an electrical current point source is used to inject electrical current (I) into the soil surface with a characteristic electric resistance or apparent resistivity (ρa, Ωm), the electrical potential (V) at a distance (ro, m) can be expressed by Eq. (1) (Kachanoski et al., 1988; Rhoades, 1976):
∞
V ¼ −∫0
2.1. Site description The study was conducted at two sandy aquifer sites in southern Keerqin, i.e., the Daqinggou Ecological Station (DES) of the Institute of
ρa I ρ I dr o ¼ a 2πr o 2πr 2o
ð1Þ
where V is the electrical potential, I is the current, ρa is the resistivity, and ro is the radius of the equipotential surface.
Fig. 1. Location of the study area and seven measurement lines at the DES (A) and the IWLIU (B).
L. Song et al. / Journal of Applied Geophysics 83 (2012) 11–18
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Fig. 2. Schematic diagram of a Wenner array: C1 and C2 represent the current electrodes, P1 and P2 represent the potential electrodes, and a represents the electrodes spacing. Adapted from Rhoades (1976).
Based on Eq. (1), the potentials at the inner electrodes (P1 and P2) can be obtained from Eqs. (2) and (3), respectively: V P1 ¼ ρa I=2π=ð1=a−1=2aÞ
ð2Þ
V P2 ¼ ρa I=2π=ð1=2a−1=aÞ
ð3Þ
where VP1 is the potential of electrode P1, VP2 is the potential of electrode P1, I is the current through electrodes P1 and P2, a is the electrode spacing (m). The potential difference between P1 and P2 can be expressed as Eq. (4): ΔV P1−P2 ¼ ρa I=2πa
ð4Þ
where ΔVP1 − P2 is the measured potential difference between electrodes P1 and P2. Therefore, the apparent resistivity (ρa) can be calculated from Eq. (5): ρa ¼2π
ΔV P1P2 a¼2πaR I
ð5Þ
where π is ≈ 3.14, and R is the measured resistance (Ω) for a given interelectrode spacing (a). For the VES interpretation of the Wenner array data, the apparent resistivity values (ρa) are plotted against half the current electrode spacing (a) on a log–log graph, and a smooth curve is drawn for each of the soundings. The sounding curves are then interpreted to determine the true soil resistivities and the thicknesses of various layers (Nejad et al., 2011), providing the basic information required to determine the turning points of the resistivity curves, i.e., the depth of the GWL. In arid and semiarid sandy regions, the soil profile can be generally divided into an upper unsaturated zone with high resistivity and a lower zone saturated with saline groundwater with low resistivity (Pozdnyakova et al., 2001). Therefore, a sharp decrease in measured resistivity during the transition from the upper zone to the lower zone, i.e., the turning point of the resistivity curve, indicates the GWL (Dege, 2011). 2.3. Geophysical data acquisition and processing Five wells were selected to assess the reliability of the VES method in determining the GWL. The first well was established at the DES; soundings were arranged in a west–east direction near well No. 1 (1 N) (Fig. 1A). GWL observations were conducted from May 05 to October 05 of 2005. Four additional wells were set up at the IWLIU. The corresponding soundings were arranged in a west–east direction
near well No. 2 (2 N), in north–south and west–east directions near well No. 3 (3 W and 3 N) and well No. 4 (4 W and 4 N), and in a north–south direction near well No. 5 (5 W). GWL observations were performed from July 01 to October 15 of 2009 (Fig. 1B). A total of five VES profiles were obtained at the DES, and twenty-five VES profiles were obtained at the IWLIU along the seven lines (1 N, 2 N, 3 W, 3 N, 4 W, 4 N and 5 W). A Yokogawa 324400 Earth Resistivity Meter was utilized to acquire the VES data from the Wenner arrays. The spacing (a) of the electrode probes was set at 1.00, 1.50, 2.00, 3.00, …, 20.00, 22.00, 24.00, …, 40.00, 44.00 m, where the depth of each electrode was set at approximately 0.20 m when the electrode spacing (a) was less than 10.00 m and at 0.30 m when the electrode spacing (a) was less than 20.00 m (Zhu et al., 2007). The GWLs in the wells were measured with a tape. The VES data for each month were measured within two days. These VES data were processed and interpreted by the method of curve matching using the IPI2Win software (Burazer et al., 2010; Nejad et al., 2011). All data were inverted with an average root mean square (RMS) error of less than 5% in each VES profile. 3. Results 3.1. The VES profiles and soil layer points The thirty VES profiles decreased or first increased and then decreased with increasing electrode spacing (i.e., becoming more conductive with depth; Fig. 3). The bulk soil was divided into different layers in the measurement range based on the results of VES data interpretation (Fig. 4). At the DES, the bulk soil in well No. 1 had one soil layer point in each VES profile (Fig. 4A). At the IWLIU, there were two to three soil layer points in wells No. 2 and No. 5 during the study period (Fig. 4B, G). The bulk soils in wells No. 3 and No. 4 had one or two soil layer points (Fig. 4C, D, E, and F). 3.2. The turning points in the VES interpretation model Based on the results of VES data interpretation, the soil layer points at the DES were the turning points in well No. 1 because there was only one soil layer point obtained from the VES interpretation. The depths of the GWLs at the DES ranged from 1.01 to 1.58 m during the study period. The corresponding GWLs manually measured ranged between 1.70 and 2.30 m. At the IWLIU, the turning points were the soil layer points inferred from the sharply decreasing curves in the apparent resistivity profiles (Fig. 4B–G), i.e., the last soil layer points or the sole soil layer points in the results of the VES data interpretations. The depths of the turning points ranged from 5.08 to 5.19 m in well No. 2, 3.59 to 4.38 m in well
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Fig. 3. Variations in the apparent resistivity in relation to the electrode spacing (a) in the thirty VES profiles in 2005 and 2009; (A) the profiles for 1N (DES); (B) the profiles for 2N; (C and D) the profiles for 3W and 3N, respectively; (E and F) the profiles for 4W and 4N, respectively; and (G) the profiles for 5W (IWLIU).
L. Song et al. / Journal of Applied Geophysics 83 (2012) 11–18
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Fig. 4. Thirty VES profiles and corresponding soil layer points near the five wells in 2005 and 2009; (A) the profiles for 1 N (DES); (B) the profiles for 2 N; (C and D) the profiles for 3 W and 3 N, respectively; (E and F) the profiles for 4 W and 4 N, respectively; and (G) the profile for 5 W (IWLIU).
No. 3, 7.44 to 8.38 m in well No. 4, and 4.94 m to 5.29 m in well No. 5. The manually measured GWLs in each well ranged between 5.00 and 5.30 m, 3.80 and 4.23 m, 8.10 and 8.26 m, and 4.80 and 5.03 m for wells 2–5, respectively (Table 1). 3.3. Relationship between estimated and measured GWLs To determine the accuracy and feasibility of GWL estimation using the VES method, the differences between the respective values and a regression calibration were determined using the data obtained from the experimental areas. The ranges of variation in the differences between the GWLs estimated by the VES method and the manually measured GWLs were from 0.22 to 1.03 m at the DES and 0.03 to
0.82 m at the IWLIU. The average variation values between the GWLs estimated by the VES method and the manually measured GWLs were 0.52 m at the DES and 0.10 m at the IWLIU (Table 1). The regression coefficient of determination was 0.06 for the linear correlation of the DES data (R2 = 0.06, P > 0.05), whereas the regression coefficient of determination was 0.97 for the linear correlation of the IWLIU data (GWLMeasured =1.01 GWLEstimated +0.05, R2 =0.97, Pb 0.05). Significance tests of the differences between the estimated and measured GWLs (Table 2) showed that there were significant differences in the DES data (P b 0.05), but no significant differences were found for the IWLIU data (P >0.05). A trend of variation with time was found for the differences between the estimated and measured GWLs at the DES (Fig. 5A), and there was a similar pattern with time at the IWLIU (Fig. 5B).
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Table 1 The GWLs estimated by the VES method, groundwater levels determined by manual measurement, and the differences between them in 2005 and 2009. Site
VES ID
DES
1N
IWLIU
2N
3W
3N
4W
4N
5W
Measuring date
GWL (m)
Difference (m)
Estimated (VES)
Measured (Well)
2005 May. 05 Jun.05 Jul.05 Aug.05 Oct.05 Mean
1.45 1.01 1.27 1.47 1.58 1.36
1.70 1.80 2.30 1.80 1.80 1.88
− 0.25 − 0.79 − 1.03 − 0.33 − 0.22 − 0.52
2009 Jul.01 Jul.28 Aug.28 Oct.15 Jul.01 Aug.28 Sep.28 Oct.15 Jul.01 Jul .28 Aug.28 Sep.28 Oct.15 Jul.01 Jul.28 Aug.28 Sep.28 Jul.01 Jul .28 Sep.28 Oct.15 Jul.01 Jul.28 Aug.28 Sep.28 Mean
5.08 5.19 5.12 5.09 3.85 3.89 3.87 4.38 4.02 4.02 3.89 3.62 3.59 8.24 8.38 8.20 7.90 8.11 7.56 8.07 7.44 4.94 5.06 5.29 4.99 5.59
5.00 5.02 5.24 5.30 3.97 4.05 4.23 4.06 3.97 3.80 4.05 4.23 4.06 8.10 8.21 8.23 8.26 8.13 8.10 8.25 8.26 4.80 4.94 5.03 4.94 5.69
0.08 0.17 − 0.12 − 0.21 − 0.12 − 0.16 − 0.36 0.32 0.05 0.22 − 0.16 − 0.61 − 0.47 0.14 0.17 − 0.03 − 0.36 − 0.02 − 0.54 − 0.18 − 0.82 0.14 0.12 0.26 0.05 − 0.10
4. Discussion 4.1. Factors influencing the estimated GWLs The VES profiles were produced by increasing the electrode spacing with depth to reflect the information on the characteristics (including depth) of different subsurface layers (Sakamoto et al., 2000). It has been demonstrated that the bulk soil can be divided into different layers based on a vertical profile of soil resistivity (Sakamoto et al., 2000; Zhu et al., 2007). In addition, coarsetextured soils exhibit a sharp change of water content between soil and groundwater, i.e., the soil resistivity sharply decreases when the sampling depth reaches GWL. Therefore, the GWL can be easily and accurately detected in theory (Liu et al., 2007). In practice, however, there are several factors influencing soil resistivity, further affecting GWL estimation. Apart from the soil water content, soil salinity, soil texture, tree root systems and soil temperature may influence soil resistivity near the surface (Sakamoto, 2001; Sudduth et al., 2003).
Fig. 5. Variations in the estimated and measured groundwater levels with time at the DES (A) and the IWLIU (B).
In this study, the soil salinity concentrations increased with depth but varied only slightly over the different months of the year (Zhu et al., 2007). Jiao (1989) measured the composition of sand particles in the plots of the study area, reporting that the composition of sand particles exhibited a homogeneous pattern. Therefore, neither soil salinity nor soil texture variations are likely to influence GWL estimation in the study area. Aside from soil properties, the distribution of tree roots may affect soil resistivity. The stands in the study area were pure P. sylvestris var. mongolica plantations, and more than 90% of their roots were distributed within the first 1.00 m below the surface (Zhu et al., 2008). Therefore, the distribution of tree roots is also unlikely to significantly affect the estimation of GWLs here. Temperature is another factor influencing the resistivity. Kachanoski et al. (2002) reported that the sensitivity of soil apparent electrical resistivity to temperature was approximately 2% per degree Celsius. In our study, temperature effects were not considered because the VES data were obtained within 2 clear days in each month. Thus, the temperature remained nearly constant over this short period. However, at the monthly scale, it is impossible to avoid the effect of temperature on field resistivity measurements. Although air temperature differed
Table 2 The results of paired-sample t-tests between GWLs estimated by the VES method and measured groundwater levels at DES and IWLIU in 2005 and 2009. Site
Measurement date
Pair
Mean
Standard deviation
T
df
Sig (2-tailed)
DES IWLIU IWLIU IWLIU IWLIU IWLIU IWLIU
May.01–Oct.01 (2005) Jul.01 (2009) Jul.28 (2009) Aug.28 (2009) Sep.28 (2009) Oct.15 (2009) Jul.01–Oct.15 (2009)
EGWL-MGWL EGWL-MGWL EGWL-MGWL EGWL-MGWL EGWL-MGWL EGWL-MGWL EGWL-MGWL
− 0.52 0.05 0.03 − 0.04 − 0.29 − 0.29 − 0.10
0.36 0.10 0.32 0.18 0.24 0.48 0.29
− 3.21 1.09 0.20 − 0.53 − 2.67 − 1.23 − 1.66
4 5 4 4 4 3 24
0.03 0.32 0.85 0.62 0.06 0.31 0.11
L. Song et al. / Journal of Applied Geophysics 83 (2012) 11–18
among the months of the study period, the soil temperature variations near the GWL were expected to be much lower than the changes in air temperature. For example, the differences in the air temperature and the soil temperature near the GWL at the IWLIU were 13 °C and 1 °C in July and October, respectively (data not shown). This difference of 1 °C would be expected to cause only approximately 2% error in these observations, which can be neglected when compared with the measurement errors. The other major factor that influences the estimation of GWLs is capillary action. Generally, there is a transitional zone or a capillary fringe in many soils, where the groundwater seeps upward from the GWL to fill soil pores. In sandy soil, this capillary fringe is narrow, and the difference in resistivity between the capillary fringe and the groundwater layer is small (Doolittle et al., 2006). Therefore, the VES method may not clearly distinguish the capillary fringe from the groundwater layer. The estimated GWL should lie between the actual GWL and the upper boundary of the capillary fringe. In addition, a deeper GWL results in a thinner capillary fringe because the height of capillary rise is affected by the soil depth above the GWL (Yang et al., 2011). For example, for the higher GWL (1.88 m) at the DES, the mean thickness of the capillary fringe was 0.62 m (data not shown), representing 33% of the average measured GWL (0.62/1.88 = 0.33). Therefore, the capillary fringe exerted a great influence on GWL estimation by the VES method at the DES. In contrast, at the IWLIU, the average GWL was deep (5.69 m), and the mean thickness of capillary fringe was 0.30 m (data not shown), which was only 5% of the average measured GWL. 4.2. Reliability of the estimated GWLs The average difference between the estimated and measured GWLs was 0.52 m at the DES (Table 1), which was a 28% error from measured GWLs with manual measurement. Paired-sample t-tests showed that there was significant difference between the estimated and measured of GWLs at the DES (Table 2). The estimated GWLs were shallower than the measured GWLs at the DES (Fig. 4A); the differences between them ranged from 0.22 to 1.03 m (mean 0.52 m), which were within the range of capillary rise in the study area (Jiang et al., 2002). In addition, the GWL at the DES (1.88 m) was shallow; thus, the height of the capillary rise was greater. Significantly different trends with time between the estimated and measured GWLs were found at the DES (Fig. 5A). These results suggested that GWL estimation with the VES method was unreliable at the DES because of the higher GWL with capillary action. At the IWLIU, the average difference between the estimated and measured GWLs at the four wells was 0.10 m, with a maximum difference of 0.82 m (Table 1), suggesting that the estimated GWLs were in close proximity to the measured GWLs. Paired sample t-tests showed that there were no significant differences between the estimated and measured GWLs (Table 2). The VES-estimated and manually measured GWLs at the IWLIU were well correlated, with a high coefficient of determination of 0.97, indicating that the GWLs estimated by the VES method were in good agreement with the manually measured GWLs. There were identical patterns with time in the variation between the estimated and measured GWLs at the IWLIU (Fig. 5B). Therefore, the significant and linear correlations demonstrated that the VES method can be used for accurate GWL estimation at the IWLIU. Shih et al. (1986) applied a GPR method to estimate GWLs and found that the differences between the estimated and observed GWLs were within 0.10 m in coarse-textured soil, with a regression coefficient of determination of 0.90. Also using a GPR method, Doolittle et al. (2006) reported that the average difference between the measured and predicted GWLs at 15 wells was 0.16 m, with a maximum difference of 0.69 m. Reutov and Shutko (1992) used a remote-sensing method to estimate GWLs; the results showed the
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dependence was reliable when the GWLs were within 2.50 m from the surface for sandy soil. In our study, the mean difference between the estimated and measured GWLs was 0.10 m at the IWLIU, and the regression coefficient of determination was 0.97. Compared with the GPR and remote sensing methods, the VES method presents advantages in measuring accuracy and depth. However, this method could not be applied at the DES because of the higher apparent GWL due to capillary action (e.g., less than 2.30 m). 5. Conclusions The apparent electrical resistivity of soil can be easily measured by a non-intrusive method, i.e., the VES method, which may be useful in the mapping of soil properties. The major advantage of the VES method for determining GWL is that this method can be used to measure a large soil volume and provide many measurements reflecting an integrated effect of soil heterogeneity rather than soil homogeneity at the field level. The GWLs estimated by the VES method were inaccurate when the GWL was high (e.g., GWL b 2.30 m) due to capillary action. In contrast, the GWLs estimated by the VES method were reasonably accurate when the GWL was sufficiently deep (e.g., GWL > 3.98 m). The VES method can reduce the required number of wells to be drilled for GWL monitoring. Therefore, it is feasible to apply the VES method for GWL estimation in sandy aquifers. GWLs between 2.30 m and 3.98 m were not studied in the present work. In addition, it must be noted that this method was only applied in sandy aquifers. The estimation of GWLs between 2.30 m and 3.98 m with the VES method and the feasibility of this method in other soil types should be studied in the future. Acknowledgments This research was supported by grants from the National Nature Science Foundation of China (31025007) and the Knowledge Innovation Program of the Chinese Academy of Sciences (KZCX1-YW-0802). We would like to acknowledge Linyou Lv from Institute of Wind-sand Land Improvement and Utilization, Zhangwu county of Liaoning province, for help in field measurement. We also thank Dr. Rucker and the anonymous reviewer for their constructive comments and editorial suggestions, which enhanced the quality of the earlier version of the manuscript. References Bian, Z.F., Lei, S.G., Inyang, H.I., Chang, L.Q., Zhang, R.C., Zhou, C.J., He, X., 2009. Integrated method of RS and GPR for monitoring the changes in the soil moisture and groundwater environment due to underground coal mining. Environmental Geology 57, 131–142 (in Chinese with English abstract). Buchanan, S., Triantafilis, J., 2009. Mapping water table depth using geophysical and environmental variables. Ground Water 47, 80–96. Burazer, M., Žitko, V., Radakovi, D., Parezanovi, M., 2010. Using geophysical methods to define the attitude and extension of water-bearing strata in the Miocene sediments of the Pannonian Basin. Journal of Applied Geophysics 72, 242–253. Clayton, C.R.I., Matthews, M.C., Simons, N.E., 1995. Site Investigation: A Handbook for Engineers. Blackwell Scientific Ltd., Oxford. Corwin, D.L., 2008. Past, present and future trends of soil electrical conductivity measurement using geophysical methods. In: Allred, B.J., Daniels, J.J., Ehsani, M.R. (Eds.), Handbook of Agricultural Geophysics. CRC Press, Boca Raton, pp. 17–44. Corwin, D.L., Lesch, S.M., 2003. Application of soil electrical conductivity to precision agriculture: theory, principles, and guidelines. Agronomy Journal 95, 455–471. Corwin, D.L., Lesch, S.M., 2005. Apparent soil electrical conductivity measurements in agriculture. Computers and Electronics in Agriculture 46, 11–43. Dege, N., 2011. Technology of Bottled Water, Third edition. Blackwell Publishing Ltd., Oxford, UK. Del Alamo, J.L., 1991. A second order gradient technique for an improved estimation of soil parameters in a two-layer earth. IEEE Transactions on Power Delivery 6, 1166–1170. DÖll, P., 2009. Vulnerability to the impact of climate change on renewable groundwater resources: a global-scale assessment. Environmental Research Letters 4, 1–12. Doolittle, J.A., Jenkinson, B., Hopkins, D., Ulmer, M., Tuttle, W., 2006. Hydropedological investigations with ground-penetrating radar (GPR): estimating water-table depths and local ground-water flow pattern in areas of coarse-textured soils. Geoderma 131, 317–329.
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Journal of Applied Geophysics journal homepage: www.elsevier.com/locate/jappgeo
Estimation of groundwater levels with vertical electrical sounding in the semiarid area of South Keerqin sandy aquifer, China Lining Song a, b, Jiaojun Zhu a,⁎, Qiaoling Yan a, Hongzhang Kang c a b c
State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China Graduate University of Chinese Academy of Sciences, Beijing 100039, China Shanghai Jiaotong University, Shanghai 200240, China
a r t i c l e
i n f o
Article history: Received 23 September 2011 Accepted 28 March 2012 Available online 6 April 2012 Keywords: Groundwater Soil electrical resistivity Manual measurement Wenner array Sandy aquifers
a b s t r a c t To develop a simple, accurate, and non-destructive method for estimating the groundwater level (GWL) in an unconfined sandy aquifer, field measurements of soil electrical resistivity were conducted at the Daqinggou Ecological Station (DES) in 2005 and the Experimental Base of the Institute of Wind-Sand Land Improvement and Utilization (IWLIU) in 2009. The resistivity data were acquired through a series of vertical electrical soundings (VES) using a Wenner array. For comparison with the VES method, the GWLs were also manually monitored in wells. The results showed that the thirty VES profiles decreased or first increased and then decreased with increasing electrode spacing (i.e., becoming more conductive with depth). The depth of the GWL was obtained by calculating the turning points, as inferred from inflections in the apparent resistivity profiles. The GWL variations between the VES method and manual measurement ranged from 0.22 to 1.03 m at the DES, with a mean value of 0.52 m, and from 0.03 to 0.82 m at the IWLIU, with a mean value of 0.10 m. The significant differences between the GWLs obtained by the VES method and manual measurement at the DES were due to the higher GWLs with capillary action; there were no significant differences in the GWLs obtained at the IWLIU. The linear regression coefficient of determination was 0.97 for the IWLIU GWL values, indicating a good agreement between the VES method and manual measurements. Therefore, we conclude that the VES method is a sound measuring tool for estimating GWLs in unconfined sandy aquifers when the GWL is sufficiently deep (e.g., GWL > 3.98 m). © 2012 Elsevier B.V. All rights reserved.
1. Introduction Groundwater is one of the most valuable natural resources (Konig and Weiss, 2009; Wood, 2002) and an important geological agent in the transport of mass and energy within the earth (Llamas, 1987), providing a wide variety of ecological and social services (DÖll, 2009; Houben and Weihe, 2010; Laio et al., 2009). In arid and semiarid areas, surface water resources are generally scarce and highly unreliable; therefore, groundwater is often the primary water resource in these areas (Scanlon et al., 2006). Groundwater level (GWL) is an essential factor related to eco-environmental problems, such as oasis degeneration caused by declining groundwater levels and land salinification due to rising groundwater levels. Thus, groundwater level monitoring is particularly important for sustainable groundwater resource management in arid and semiarid areas. The traditional method for monitoring GWL is the collection of measurements from a limited number of often widely spaced piezometers or observation wells (Doolittle et al., 2006). This method ⁎ Corresponding author at: Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang110016. Tel.: +86 24 83970342; fax: +86 24 83970300. E-mail address: [email protected] (J. Zhu). 0926-9851/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.jappgeo.2012.03.011
requires large amounts of manpower and material resources; limitations in the number of wells drilled may thus lead to the inaccurate estimation of groundwater levels (Bian et al., 2009; Buchanan and Triantafilis, 2009). Additionally, extensive well drilling may result in damage to the site, especially in arid and semiarid sandy areas (Tabbagh et al., 2000). Therefore, traditional methods cannot typically be applied to monitor the GWL efficiently in such areas. In contrast, geophysical methods are currently receiving increasing attention for GWL monitoring due to their noninvasive nature and the ability to investigate an entire soil volume (Tabbagh et al., 2000). Among these geophysical methods, ground-penetrating radar (GPR), remote sensing, and electrical resistivity have been widely used in groundwater exploration. GPR can provide high-resolution subsurface images of the shallow subsurface (Doolittle et al., 2006; Lambot et al., 2008; Pyke et al., 2008; Rucker and Ferré, 2003); however, this method is not applicable when the GWL of a study area is deeper than 30 m (Liang et al., 2002). Remote sensing has the advantages of spatial, spectral and temporal availabilities and the manipulation of data covering large areas in a short time (Sener et al., 2005), but the precision of remote sensing is low by visual interpretation or conventional statistical methods, which limits its application in GWL estimation.
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Originally investigated for grounding and lightning prevention/ protection systems, soil electrical resistivity (or soil resistivity) is an important parameter that reflects soil physical properties and subsurface structure (Sakamoto, 2001; Sakamoto and Sekiguchi, 2001; Samouëlian et al., 2005; Zhu et al., 2005; 2007). Vertical electrical sounding (VES) is a geoelectrical method for measuring vertical alterations in soil resistivity, which has been recognized as being well suited for the subsurface investigation of geologic environments (Nejad, 2009). Generally, there are three electrode configurations that are applied in VES profiling: the Wenner, Schlumberger, and dipole–dipole arrays (Rucker et al., 2009). Among these, the Wenner array has the simplest geometry (Clayton et al., 1995) and is quicker and easier to operate than the Schlumberger array. The dipole–dipole array method yields lower signal strength compared with the Wenner and Schlumberger arrays (Loke, 2001). In addition, the Wenner array is the most accurate for the measurement of apparent resistivity (Del Alamo, 1991; Gonos and Stathopulos, 2005) and is useful in resolving vertical resistivity changes with depth (Loke, 2001). Therefore, VES with the Wenner array is widely used in soil science and groundwater investigation (Corwin and Lesch, 2005) for detecting soil salinity in precision agriculture (Corwin and Lesch, 2003), investigating groundwater pollution (Urish, 1983), mapping groundwater flow direction and velocity (White, 1994), and detecting soil cracking (Samouëlian et al., 2003). In previous studies, VES using Wenner arrays has been applied to determine soil resistivity (Zhu et al., 2005) and estimate soil water content within 1.50 m from the surface in pine plantations in sandy soils (Zhu et al., 2007). However, little information exists regarding whether VES with a Wenner array can be applied to the estimation of GWL in a sandy aquifer. The purpose of this study was to evaluate the use of VES with a Wenner array for the estimation of the GWL in a sandy aquifer and to determine the accuracy and usefulness of this method. 2. Materials and methods
Applied Ecology, Chinese Academy of Sciences (42°52′ N, 122°55′ E) and the Experimental Base of the Institute of Wind-Sand Land Improvement and Utilization (IWLIU), Liaoning Province, China (42°43′ N, 122°22′ E) (Fig. 1). The two sites are 25 km apart. The mean annual air temperature at both sites is 6.1 °C, and the minimum and maximum air temperatures (1954–2010) are −29.5 °C and 37.2 °C, respectively. The annual precipitation at both sites is 474 mm, with more than 60% occurring during June and August. The major soil type is classified in the Semiaripsamment taxonomic group, which is developed from sandy parent material through wind action (Zeng et al., 2009; Zhu et al., 2008). The vegetation in the study areas consists of Pinus sylvestris var. mongolica plantations and annual herbs (Zhao et al., 2004; Zhu et al., 2005). Based on landforms, vegetation cover types and soil characteristics, the sandy areas in the study areas were classified into low aeolian dunes, low mountains and hills, and high elevation alluvial flats. The current average groundwater levels are approximately 2.00 m and 5.54 m at the DES and the IWLIU, respectively. 2.2. Theory In the Wenner array, four electrodes were injected into the soil surface along a straight line at predetermined distances (a) (Fig. 2). The electrical resistance to current flow was measured between a pair of inner electrodes (P1 and P2 in Fig. 2) while electrical current flowed through the soil between a pair of outer electrodes (C1 and C2 in Fig. 2) (Corwin, 2008; Rhoades, 1976; Zhu et al., 2007). When an electrical current point source is used to inject electrical current (I) into the soil surface with a characteristic electric resistance or apparent resistivity (ρa, Ωm), the electrical potential (V) at a distance (ro, m) can be expressed by Eq. (1) (Kachanoski et al., 1988; Rhoades, 1976):
∞
V ¼ −∫0
2.1. Site description The study was conducted at two sandy aquifer sites in southern Keerqin, i.e., the Daqinggou Ecological Station (DES) of the Institute of
ρa I ρ I dr o ¼ a 2πr o 2πr 2o
ð1Þ
where V is the electrical potential, I is the current, ρa is the resistivity, and ro is the radius of the equipotential surface.
Fig. 1. Location of the study area and seven measurement lines at the DES (A) and the IWLIU (B).
L. Song et al. / Journal of Applied Geophysics 83 (2012) 11–18
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Fig. 2. Schematic diagram of a Wenner array: C1 and C2 represent the current electrodes, P1 and P2 represent the potential electrodes, and a represents the electrodes spacing. Adapted from Rhoades (1976).
Based on Eq. (1), the potentials at the inner electrodes (P1 and P2) can be obtained from Eqs. (2) and (3), respectively: V P1 ¼ ρa I=2π=ð1=a−1=2aÞ
ð2Þ
V P2 ¼ ρa I=2π=ð1=2a−1=aÞ
ð3Þ
where VP1 is the potential of electrode P1, VP2 is the potential of electrode P1, I is the current through electrodes P1 and P2, a is the electrode spacing (m). The potential difference between P1 and P2 can be expressed as Eq. (4): ΔV P1−P2 ¼ ρa I=2πa
ð4Þ
where ΔVP1 − P2 is the measured potential difference between electrodes P1 and P2. Therefore, the apparent resistivity (ρa) can be calculated from Eq. (5): ρa ¼2π
ΔV P1P2 a¼2πaR I
ð5Þ
where π is ≈ 3.14, and R is the measured resistance (Ω) for a given interelectrode spacing (a). For the VES interpretation of the Wenner array data, the apparent resistivity values (ρa) are plotted against half the current electrode spacing (a) on a log–log graph, and a smooth curve is drawn for each of the soundings. The sounding curves are then interpreted to determine the true soil resistivities and the thicknesses of various layers (Nejad et al., 2011), providing the basic information required to determine the turning points of the resistivity curves, i.e., the depth of the GWL. In arid and semiarid sandy regions, the soil profile can be generally divided into an upper unsaturated zone with high resistivity and a lower zone saturated with saline groundwater with low resistivity (Pozdnyakova et al., 2001). Therefore, a sharp decrease in measured resistivity during the transition from the upper zone to the lower zone, i.e., the turning point of the resistivity curve, indicates the GWL (Dege, 2011). 2.3. Geophysical data acquisition and processing Five wells were selected to assess the reliability of the VES method in determining the GWL. The first well was established at the DES; soundings were arranged in a west–east direction near well No. 1 (1 N) (Fig. 1A). GWL observations were conducted from May 05 to October 05 of 2005. Four additional wells were set up at the IWLIU. The corresponding soundings were arranged in a west–east direction
near well No. 2 (2 N), in north–south and west–east directions near well No. 3 (3 W and 3 N) and well No. 4 (4 W and 4 N), and in a north–south direction near well No. 5 (5 W). GWL observations were performed from July 01 to October 15 of 2009 (Fig. 1B). A total of five VES profiles were obtained at the DES, and twenty-five VES profiles were obtained at the IWLIU along the seven lines (1 N, 2 N, 3 W, 3 N, 4 W, 4 N and 5 W). A Yokogawa 324400 Earth Resistivity Meter was utilized to acquire the VES data from the Wenner arrays. The spacing (a) of the electrode probes was set at 1.00, 1.50, 2.00, 3.00, …, 20.00, 22.00, 24.00, …, 40.00, 44.00 m, where the depth of each electrode was set at approximately 0.20 m when the electrode spacing (a) was less than 10.00 m and at 0.30 m when the electrode spacing (a) was less than 20.00 m (Zhu et al., 2007). The GWLs in the wells were measured with a tape. The VES data for each month were measured within two days. These VES data were processed and interpreted by the method of curve matching using the IPI2Win software (Burazer et al., 2010; Nejad et al., 2011). All data were inverted with an average root mean square (RMS) error of less than 5% in each VES profile. 3. Results 3.1. The VES profiles and soil layer points The thirty VES profiles decreased or first increased and then decreased with increasing electrode spacing (i.e., becoming more conductive with depth; Fig. 3). The bulk soil was divided into different layers in the measurement range based on the results of VES data interpretation (Fig. 4). At the DES, the bulk soil in well No. 1 had one soil layer point in each VES profile (Fig. 4A). At the IWLIU, there were two to three soil layer points in wells No. 2 and No. 5 during the study period (Fig. 4B, G). The bulk soils in wells No. 3 and No. 4 had one or two soil layer points (Fig. 4C, D, E, and F). 3.2. The turning points in the VES interpretation model Based on the results of VES data interpretation, the soil layer points at the DES were the turning points in well No. 1 because there was only one soil layer point obtained from the VES interpretation. The depths of the GWLs at the DES ranged from 1.01 to 1.58 m during the study period. The corresponding GWLs manually measured ranged between 1.70 and 2.30 m. At the IWLIU, the turning points were the soil layer points inferred from the sharply decreasing curves in the apparent resistivity profiles (Fig. 4B–G), i.e., the last soil layer points or the sole soil layer points in the results of the VES data interpretations. The depths of the turning points ranged from 5.08 to 5.19 m in well No. 2, 3.59 to 4.38 m in well
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Fig. 3. Variations in the apparent resistivity in relation to the electrode spacing (a) in the thirty VES profiles in 2005 and 2009; (A) the profiles for 1N (DES); (B) the profiles for 2N; (C and D) the profiles for 3W and 3N, respectively; (E and F) the profiles for 4W and 4N, respectively; and (G) the profiles for 5W (IWLIU).
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Fig. 4. Thirty VES profiles and corresponding soil layer points near the five wells in 2005 and 2009; (A) the profiles for 1 N (DES); (B) the profiles for 2 N; (C and D) the profiles for 3 W and 3 N, respectively; (E and F) the profiles for 4 W and 4 N, respectively; and (G) the profile for 5 W (IWLIU).
No. 3, 7.44 to 8.38 m in well No. 4, and 4.94 m to 5.29 m in well No. 5. The manually measured GWLs in each well ranged between 5.00 and 5.30 m, 3.80 and 4.23 m, 8.10 and 8.26 m, and 4.80 and 5.03 m for wells 2–5, respectively (Table 1). 3.3. Relationship between estimated and measured GWLs To determine the accuracy and feasibility of GWL estimation using the VES method, the differences between the respective values and a regression calibration were determined using the data obtained from the experimental areas. The ranges of variation in the differences between the GWLs estimated by the VES method and the manually measured GWLs were from 0.22 to 1.03 m at the DES and 0.03 to
0.82 m at the IWLIU. The average variation values between the GWLs estimated by the VES method and the manually measured GWLs were 0.52 m at the DES and 0.10 m at the IWLIU (Table 1). The regression coefficient of determination was 0.06 for the linear correlation of the DES data (R2 = 0.06, P > 0.05), whereas the regression coefficient of determination was 0.97 for the linear correlation of the IWLIU data (GWLMeasured =1.01 GWLEstimated +0.05, R2 =0.97, Pb 0.05). Significance tests of the differences between the estimated and measured GWLs (Table 2) showed that there were significant differences in the DES data (P b 0.05), but no significant differences were found for the IWLIU data (P >0.05). A trend of variation with time was found for the differences between the estimated and measured GWLs at the DES (Fig. 5A), and there was a similar pattern with time at the IWLIU (Fig. 5B).
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Table 1 The GWLs estimated by the VES method, groundwater levels determined by manual measurement, and the differences between them in 2005 and 2009. Site
VES ID
DES
1N
IWLIU
2N
3W
3N
4W
4N
5W
Measuring date
GWL (m)
Difference (m)
Estimated (VES)
Measured (Well)
2005 May. 05 Jun.05 Jul.05 Aug.05 Oct.05 Mean
1.45 1.01 1.27 1.47 1.58 1.36
1.70 1.80 2.30 1.80 1.80 1.88
− 0.25 − 0.79 − 1.03 − 0.33 − 0.22 − 0.52
2009 Jul.01 Jul.28 Aug.28 Oct.15 Jul.01 Aug.28 Sep.28 Oct.15 Jul.01 Jul .28 Aug.28 Sep.28 Oct.15 Jul.01 Jul.28 Aug.28 Sep.28 Jul.01 Jul .28 Sep.28 Oct.15 Jul.01 Jul.28 Aug.28 Sep.28 Mean
5.08 5.19 5.12 5.09 3.85 3.89 3.87 4.38 4.02 4.02 3.89 3.62 3.59 8.24 8.38 8.20 7.90 8.11 7.56 8.07 7.44 4.94 5.06 5.29 4.99 5.59
5.00 5.02 5.24 5.30 3.97 4.05 4.23 4.06 3.97 3.80 4.05 4.23 4.06 8.10 8.21 8.23 8.26 8.13 8.10 8.25 8.26 4.80 4.94 5.03 4.94 5.69
0.08 0.17 − 0.12 − 0.21 − 0.12 − 0.16 − 0.36 0.32 0.05 0.22 − 0.16 − 0.61 − 0.47 0.14 0.17 − 0.03 − 0.36 − 0.02 − 0.54 − 0.18 − 0.82 0.14 0.12 0.26 0.05 − 0.10
4. Discussion 4.1. Factors influencing the estimated GWLs The VES profiles were produced by increasing the electrode spacing with depth to reflect the information on the characteristics (including depth) of different subsurface layers (Sakamoto et al., 2000). It has been demonstrated that the bulk soil can be divided into different layers based on a vertical profile of soil resistivity (Sakamoto et al., 2000; Zhu et al., 2007). In addition, coarsetextured soils exhibit a sharp change of water content between soil and groundwater, i.e., the soil resistivity sharply decreases when the sampling depth reaches GWL. Therefore, the GWL can be easily and accurately detected in theory (Liu et al., 2007). In practice, however, there are several factors influencing soil resistivity, further affecting GWL estimation. Apart from the soil water content, soil salinity, soil texture, tree root systems and soil temperature may influence soil resistivity near the surface (Sakamoto, 2001; Sudduth et al., 2003).
Fig. 5. Variations in the estimated and measured groundwater levels with time at the DES (A) and the IWLIU (B).
In this study, the soil salinity concentrations increased with depth but varied only slightly over the different months of the year (Zhu et al., 2007). Jiao (1989) measured the composition of sand particles in the plots of the study area, reporting that the composition of sand particles exhibited a homogeneous pattern. Therefore, neither soil salinity nor soil texture variations are likely to influence GWL estimation in the study area. Aside from soil properties, the distribution of tree roots may affect soil resistivity. The stands in the study area were pure P. sylvestris var. mongolica plantations, and more than 90% of their roots were distributed within the first 1.00 m below the surface (Zhu et al., 2008). Therefore, the distribution of tree roots is also unlikely to significantly affect the estimation of GWLs here. Temperature is another factor influencing the resistivity. Kachanoski et al. (2002) reported that the sensitivity of soil apparent electrical resistivity to temperature was approximately 2% per degree Celsius. In our study, temperature effects were not considered because the VES data were obtained within 2 clear days in each month. Thus, the temperature remained nearly constant over this short period. However, at the monthly scale, it is impossible to avoid the effect of temperature on field resistivity measurements. Although air temperature differed
Table 2 The results of paired-sample t-tests between GWLs estimated by the VES method and measured groundwater levels at DES and IWLIU in 2005 and 2009. Site
Measurement date
Pair
Mean
Standard deviation
T
df
Sig (2-tailed)
DES IWLIU IWLIU IWLIU IWLIU IWLIU IWLIU
May.01–Oct.01 (2005) Jul.01 (2009) Jul.28 (2009) Aug.28 (2009) Sep.28 (2009) Oct.15 (2009) Jul.01–Oct.15 (2009)
EGWL-MGWL EGWL-MGWL EGWL-MGWL EGWL-MGWL EGWL-MGWL EGWL-MGWL EGWL-MGWL
− 0.52 0.05 0.03 − 0.04 − 0.29 − 0.29 − 0.10
0.36 0.10 0.32 0.18 0.24 0.48 0.29
− 3.21 1.09 0.20 − 0.53 − 2.67 − 1.23 − 1.66
4 5 4 4 4 3 24
0.03 0.32 0.85 0.62 0.06 0.31 0.11
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among the months of the study period, the soil temperature variations near the GWL were expected to be much lower than the changes in air temperature. For example, the differences in the air temperature and the soil temperature near the GWL at the IWLIU were 13 °C and 1 °C in July and October, respectively (data not shown). This difference of 1 °C would be expected to cause only approximately 2% error in these observations, which can be neglected when compared with the measurement errors. The other major factor that influences the estimation of GWLs is capillary action. Generally, there is a transitional zone or a capillary fringe in many soils, where the groundwater seeps upward from the GWL to fill soil pores. In sandy soil, this capillary fringe is narrow, and the difference in resistivity between the capillary fringe and the groundwater layer is small (Doolittle et al., 2006). Therefore, the VES method may not clearly distinguish the capillary fringe from the groundwater layer. The estimated GWL should lie between the actual GWL and the upper boundary of the capillary fringe. In addition, a deeper GWL results in a thinner capillary fringe because the height of capillary rise is affected by the soil depth above the GWL (Yang et al., 2011). For example, for the higher GWL (1.88 m) at the DES, the mean thickness of the capillary fringe was 0.62 m (data not shown), representing 33% of the average measured GWL (0.62/1.88 = 0.33). Therefore, the capillary fringe exerted a great influence on GWL estimation by the VES method at the DES. In contrast, at the IWLIU, the average GWL was deep (5.69 m), and the mean thickness of capillary fringe was 0.30 m (data not shown), which was only 5% of the average measured GWL. 4.2. Reliability of the estimated GWLs The average difference between the estimated and measured GWLs was 0.52 m at the DES (Table 1), which was a 28% error from measured GWLs with manual measurement. Paired-sample t-tests showed that there was significant difference between the estimated and measured of GWLs at the DES (Table 2). The estimated GWLs were shallower than the measured GWLs at the DES (Fig. 4A); the differences between them ranged from 0.22 to 1.03 m (mean 0.52 m), which were within the range of capillary rise in the study area (Jiang et al., 2002). In addition, the GWL at the DES (1.88 m) was shallow; thus, the height of the capillary rise was greater. Significantly different trends with time between the estimated and measured GWLs were found at the DES (Fig. 5A). These results suggested that GWL estimation with the VES method was unreliable at the DES because of the higher GWL with capillary action. At the IWLIU, the average difference between the estimated and measured GWLs at the four wells was 0.10 m, with a maximum difference of 0.82 m (Table 1), suggesting that the estimated GWLs were in close proximity to the measured GWLs. Paired sample t-tests showed that there were no significant differences between the estimated and measured GWLs (Table 2). The VES-estimated and manually measured GWLs at the IWLIU were well correlated, with a high coefficient of determination of 0.97, indicating that the GWLs estimated by the VES method were in good agreement with the manually measured GWLs. There were identical patterns with time in the variation between the estimated and measured GWLs at the IWLIU (Fig. 5B). Therefore, the significant and linear correlations demonstrated that the VES method can be used for accurate GWL estimation at the IWLIU. Shih et al. (1986) applied a GPR method to estimate GWLs and found that the differences between the estimated and observed GWLs were within 0.10 m in coarse-textured soil, with a regression coefficient of determination of 0.90. Also using a GPR method, Doolittle et al. (2006) reported that the average difference between the measured and predicted GWLs at 15 wells was 0.16 m, with a maximum difference of 0.69 m. Reutov and Shutko (1992) used a remote-sensing method to estimate GWLs; the results showed the
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dependence was reliable when the GWLs were within 2.50 m from the surface for sandy soil. In our study, the mean difference between the estimated and measured GWLs was 0.10 m at the IWLIU, and the regression coefficient of determination was 0.97. Compared with the GPR and remote sensing methods, the VES method presents advantages in measuring accuracy and depth. However, this method could not be applied at the DES because of the higher apparent GWL due to capillary action (e.g., less than 2.30 m). 5. Conclusions The apparent electrical resistivity of soil can be easily measured by a non-intrusive method, i.e., the VES method, which may be useful in the mapping of soil properties. The major advantage of the VES method for determining GWL is that this method can be used to measure a large soil volume and provide many measurements reflecting an integrated effect of soil heterogeneity rather than soil homogeneity at the field level. The GWLs estimated by the VES method were inaccurate when the GWL was high (e.g., GWL b 2.30 m) due to capillary action. In contrast, the GWLs estimated by the VES method were reasonably accurate when the GWL was sufficiently deep (e.g., GWL > 3.98 m). The VES method can reduce the required number of wells to be drilled for GWL monitoring. Therefore, it is feasible to apply the VES method for GWL estimation in sandy aquifers. GWLs between 2.30 m and 3.98 m were not studied in the present work. In addition, it must be noted that this method was only applied in sandy aquifers. The estimation of GWLs between 2.30 m and 3.98 m with the VES method and the feasibility of this method in other soil types should be studied in the future. Acknowledgments This research was supported by grants from the National Nature Science Foundation of China (31025007) and the Knowledge Innovation Program of the Chinese Academy of Sciences (KZCX1-YW-0802). We would like to acknowledge Linyou Lv from Institute of Wind-sand Land Improvement and Utilization, Zhangwu county of Liaoning province, for help in field measurement. We also thank Dr. Rucker and the anonymous reviewer for their constructive comments and editorial suggestions, which enhanced the quality of the earlier version of the manuscript. References Bian, Z.F., Lei, S.G., Inyang, H.I., Chang, L.Q., Zhang, R.C., Zhou, C.J., He, X., 2009. Integrated method of RS and GPR for monitoring the changes in the soil moisture and groundwater environment due to underground coal mining. Environmental Geology 57, 131–142 (in Chinese with English abstract). Buchanan, S., Triantafilis, J., 2009. Mapping water table depth using geophysical and environmental variables. Ground Water 47, 80–96. Burazer, M., Žitko, V., Radakovi, D., Parezanovi, M., 2010. Using geophysical methods to define the attitude and extension of water-bearing strata in the Miocene sediments of the Pannonian Basin. Journal of Applied Geophysics 72, 242–253. Clayton, C.R.I., Matthews, M.C., Simons, N.E., 1995. Site Investigation: A Handbook for Engineers. Blackwell Scientific Ltd., Oxford. Corwin, D.L., 2008. Past, present and future trends of soil electrical conductivity measurement using geophysical methods. In: Allred, B.J., Daniels, J.J., Ehsani, M.R. (Eds.), Handbook of Agricultural Geophysics. CRC Press, Boca Raton, pp. 17–44. Corwin, D.L., Lesch, S.M., 2003. Application of soil electrical conductivity to precision agriculture: theory, principles, and guidelines. Agronomy Journal 95, 455–471. Corwin, D.L., Lesch, S.M., 2005. Apparent soil electrical conductivity measurements in agriculture. Computers and Electronics in Agriculture 46, 11–43. Dege, N., 2011. Technology of Bottled Water, Third edition. Blackwell Publishing Ltd., Oxford, UK. Del Alamo, J.L., 1991. A second order gradient technique for an improved estimation of soil parameters in a two-layer earth. IEEE Transactions on Power Delivery 6, 1166–1170. DÖll, P., 2009. Vulnerability to the impact of climate change on renewable groundwater resources: a global-scale assessment. Environmental Research Letters 4, 1–12. Doolittle, J.A., Jenkinson, B., Hopkins, D., Ulmer, M., Tuttle, W., 2006. Hydropedological investigations with ground-penetrating radar (GPR): estimating water-table depths and local ground-water flow pattern in areas of coarse-textured soils. Geoderma 131, 317–329.
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